I've been using Sprinto for a few months now, mainly for its compliance mapping features. It's decent for that. But their built-in cloud infrastructure scanning? Frankly, it's a checkbox exercise. It gives you a high-level "you have an S3 bucket open to the world" alert, but it doesn't dig deep enough for my liking.
I needed something that could integrate with our CI/CD pipeline and fail a build if a specific, critical misconfiguration was detected. Sprinto's API is robust enough to build on top of, so I did just that.
Here's the core of my custom control. It's a Python script that runs in our deployment workflow, calls the AWS Config API directly for deeper context, and then creates a finding in Sprinto via webhook.
```python
import boto3
import requests
import json
# Check for overly permissive Security Groups
ec2 = boto3.client('ec2')
response = ec2.describe_security_groups(Filters=[
{'Name': 'ip-permission.cidr', 'Values': ['0.0.0.0/0']},
{'Name': 'ip-permission.from-port', 'Values': ['22']} # SSH
])
non_compliant_resources = []
for sg in response['SecurityGroups']:
for perm in sg['IpPermissions']:
if 'FromPort' in perm and perm['FromPort'] == 22:
for ip_range in perm.get('IpRanges', []):
if ip_range.get('CidrIp') == '0.0.0.0/0':
non_compliant_resources.append({
"resource_id": sg['GroupId'],
"resource_type": "AWS::EC2::SecurityGroup",
"violation": "SSH open to internet (0.0.0.0/0)"
})
# Post findings to Sprinto webhook
if non_compliant_resources:
sprinto_payload = {
"control_id": "custom_ssh_exposure",
"control_name": "Custom: Detect SSH Exposed to Internet",
"severity": "high",
"resources": non_compliant_resources,
"scan_origin": "ci_cd_pipeline"
}
requests.post(os.environ['SPRINTO_WEBHOOK_URL'], json=sprinto_payload)
sys.exit(1) # Fail the build
```
The key advantages over just using Sprinto's native scanner:
* **Context-aware:** It checks specifically for SSH (port 22) open to the world, not just any open port.
* **Pipeline integration:** It fails the build instantly, preventing the infra change from being applied.
* **Rich data:** I can format the finding exactly how my team needs to see it, linking directly to the resource.
This approach treats Sprinto more as a findings aggregator and reporting dashboard, while the heavy lifting of detection is done by purpose-built scripts. Their generic cloud scan is too slow and too vague for actual security gates.
Has anyone else built custom controls on top of Sprinto? I'm curious how you're handling the data mapping back to compliance frameworks, because that part is still a bit manual for me.
-- bb
-- bb
I appreciate you sharing this. It's a clever way to extend a platform's core value with your own deeper logic. This gets at a common tension, though: how far should a vendor's built-in controls go versus enabling this kind of DIY extension?
Your approach is powerful, but one thing I've seen teams struggle with is the maintenance burden. You're now responsible for the logic, the boto3 calls, and the webhook integration if Sprinto's API changes. It's a tradeoff between depth and operational overhead. Have you thought about how you'll manage updates or hand this off to another team member?
Oh, the maintenance tax is real. I've got a whole folder of similar glue scripts that I treat like pets, not cattle.
But the vendor's depth vs. DIY trade-off cuts both ways. You're right that *they* could break my integration, but *I* can fix it in an hour when their roadmap ignores a critical AWS service for six months. My script got our GuardDuty findings parsed and into Sprinto last quarter. Their "deeper controls" update is still TBD.
Handoff is the real pain point. I solved it by wrapping everything in a small Lambda with decent logging and a README that's basically a troubleshooting guide. If I get hit by a bus, they can at least turn it off.
That "hit by a bus" guide is such a key point. Documenting how to turn it off is almost more important than how it runs.
But it makes me wonder, how do you budget time for this? I'm looking at similar tools, and I'm trying to weigh if the vendor's roadmap speed is worth the subscription cost, versus the hidden internal hours for maintaining these scripts. Do you track those hours, or is it just accepted as part of the role?
Tracking those internal hours? I have a cost allocation tag for it. I call it `project:vendor-workaround`. It shows up on my monthly cloud bill review, and it's a great way to make the "hidden" cost painfully visible to management.
It's never just accepted as part of the role, it's a line-item argument. When finance asks why that line is growing, I can point directly to the vendor's missing feature backlog. That's how you get budget for a better tool, or finally pressure the vendor to ship.
The real trick is knowing when the script's monthly "maintenance tax" exceeds the vendor's subscription premium. I've killed more scripts than I've kept once that crossover happens.
Exactly. That hidden cost is the whole business case. It's rarely tracked, so it's never challenged.
If you're evaluating a tool, you have to build that maintenance tax into the TCO from day one. Project it for 12 months. When you present that to management, the decision between a more expensive "complete" tool and a cheaper one you have to extend becomes obvious.
The issue is most teams accept it as unpaid overtime, which only guarantees the problem continues. Formalize it. Log the hours, tag the spend, make it a line item. Then you're not arguing opinions, you're comparing actual budgets.
—AF